<span id="fpn9h"><noframes id="fpn9h"><span id="fpn9h"></span>
<span id="fpn9h"><noframes id="fpn9h">
<th id="fpn9h"></th>
<strike id="fpn9h"><noframes id="fpn9h"><strike id="fpn9h"></strike>
<th id="fpn9h"><noframes id="fpn9h">
<span id="fpn9h"><video id="fpn9h"></video></span>
<ruby id="fpn9h"></ruby>
<strike id="fpn9h"><noframes id="fpn9h"><span id="fpn9h"></span>

可搜索加密及其驅動的SQL隱私數據庫設計

Privacy-preserving SQL database driven by searchable encryption

  • 摘要: 隱私數據庫是促進國家大數據戰略與數據要素市場發展中構建數據開放、共享及治理體系的重要手段,而可搜索加密作為實現隱私數據庫的重要密碼技術,仍存在缺乏靈活檢索機制及抗量子安全等問題,也難以適配關系數據庫中的結構化查詢語言(SQL)查詢機制. 在對可搜索加密技術現狀分析基礎上,本文設計了可適配關系數據庫SQL查詢語言的隱私數據庫架構,客戶端引入隱私SQL引擎將索引和數據字段轉變為密文狀態;用戶發起查詢請求時,該引擎可依據查詢策略生成查詢憑證,隱私數據庫進而依據憑證對密態索引進行密碼化檢索,匹配成功的密態數據字段可由用戶私鑰進行解密. 進一步,本文在格密碼體制下利用理想格上短整數解(R-SIS)和帶誤差學習(R-LWE)困難問題,設計了檢索策略的屬性基可搜索加密(RP-ABSE)方案用以支持上述隱私數據庫密碼系統的構建. 該方案將查詢策略與查詢憑證相綁定,確保密文數據的索引可依據查詢策略進行細粒度密碼化檢索;同時,引入小策略矩陣(SPM)來優化安全查詢策略生成,降低索引匹配過程中累積誤差. 由安全性證明可知,查詢憑證滿足在選擇策略攻擊下的不可偽造性(EU-CPA),所提系統滿足在帶有策略和標識查詢的選擇明文攻擊下的語義安全性(IND-PIQ-CPA).

     

    Abstract: In the era of national big data strategies and burgeoning data markets, privacy-preserving databases play a crucial role in establishing an environment that is open, shared, and governed. Central to the construction of such databases is searchable encryption (SE), a fundamental cryptographic technology that enables efficient searching within encrypted data without the need for decryption. Among various SE schemes, attribute-based SE (ABSE) provides advantages in access control, data authenticity, and retrieval efficiency. However, a substantial limitation of most current ABSE implementations is their inability to support flexible SQL query methods in relational databases, as well as more granular query policies. Moreover, the reliance on traditional algebraic structures, such as bilinear pairing, renders these systems susceptible to quantum computing attacks. To address these challenges, this study presents a novel architecture for privacy-preserving databases that accommodates the SQL query language used in relational databases. This architecture is divided into two parts: clients and cloud outsourcing services. Within this framework, all data are in a ciphertext form outside of client access, and the data table in the cloud-based privacy-preserving database comprises four types of fields: public, encrypted index, encrypted data, and confidential fields. Upon receiving an SQL query from a user, the privacy-preserving SQL engine translates it into a private SQL language. This enables cryptographic retrieval of the encrypted index fields by converting the SQL query policy into several query credentials linked with the policy. These credentials facilitate the retrieval of encrypted data fields from the database, matching their index with the policy. The retrieved encrypted data fields can then be decrypted using the user’s private key at the client’s end for confirming the user’s identity. To provide cryptographic support for this privacy-preserving database architecture, we propose a retrieval-policy ABSE (RP-ABSE) scheme built upon a key-policy attribute-based encryption framework. The security of RP-ABSE is underpinned by a hard problem over an ideal lattice, particularly short integer solutions and learning with error problems. A notable advancement in this scheme is the binding of the secure query policy to the query credentials rather than the encrypted index fields. This binding ensures that encrypted data can be cryptographically retrieved by different query policies, eliminating the need for updating the encrypted data when query policies change. Simultaneously, we introduce a small policy matrix to optimize the generation of secure query policies and mitigate cumulative errors during the index matching process. Ultimately, this study proves that the query credential satisfies unforgeability under chosen policy attacks and that the RP-ABSE scheme achieves semantic security under chosen plaintext attacks involving policy and identity queries. Therefore, the proposed privacy-preserving database architecture offers crucial technique support for the development of data market mechanisms and data governance systems.

     

/

返回文章
返回
<span id="fpn9h"><noframes id="fpn9h"><span id="fpn9h"></span>
<span id="fpn9h"><noframes id="fpn9h">
<th id="fpn9h"></th>
<strike id="fpn9h"><noframes id="fpn9h"><strike id="fpn9h"></strike>
<th id="fpn9h"><noframes id="fpn9h">
<span id="fpn9h"><video id="fpn9h"></video></span>
<ruby id="fpn9h"></ruby>
<strike id="fpn9h"><noframes id="fpn9h"><span id="fpn9h"></span>
www.77susu.com